R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1
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+ ,0
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+ ,0
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+ ,0
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+ ,0
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+ ,0
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+ ,0
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+ ,0
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+ ,0
+ ,0
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+ ,0
+ ,62792
+ ,35
+ ,0
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+ ,0
+ ,15
+ ,0
+ ,51
+ ,0
+ ,30884
+ ,0
+ ,0
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+ ,0
+ ,72535
+ ,14
+ ,0
+ ,17
+ ,0
+ ,16
+ ,0
+ ,39
+ ,0
+ ,19540
+ ,0)
+ ,dim=c(14
+ ,289)
+ ,dimnames=list(c('Pop'
+ ,'T'
+ ,'Pop_t'
+ ,'Time_in_rfc'
+ ,'Logins'
+ ,'Logins_P'
+ ,'Blogged_computations'
+ ,'Blogged_computations_P'
+ ,'Compendiums_reviewed'
+ ,'Compendiums_reviewed_P'
+ ,'Feedback_messages_p120'
+ ,'Feedback_messages_p120_P'
+ ,'Total_number_of_characters'
+ ,'Total_number_of_characters_P')
+ ,1:289))
> y <- array(NA,dim=c(14,289),dimnames=list(c('Pop','T','Pop_t','Time_in_rfc','Logins','Logins_P','Blogged_computations','Blogged_computations_P','Compendiums_reviewed','Compendiums_reviewed_P','Feedback_messages_p120','Feedback_messages_p120_P','Total_number_of_characters','Total_number_of_characters_P'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '4'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Time_in_rfc Pop T Pop_t Logins Logins_P Blogged_computations
1 210907 1 1 1 56 56 79
2 120982 1 2 2 56 56 58
3 176508 1 3 3 54 54 60
4 179321 1 4 4 89 89 108
5 123185 1 5 5 40 40 49
6 52746 1 6 6 25 25 0
7 385534 1 7 7 92 92 121
8 33170 1 8 8 18 18 1
9 149061 1 9 9 44 44 43
10 165446 1 10 10 33 33 69
11 237213 1 11 11 84 84 78
12 173326 1 12 12 88 88 86
13 133131 1 13 13 55 55 44
14 258873 1 14 14 60 60 104
15 180083 1 15 15 66 66 63
16 324799 1 16 16 154 154 158
17 230964 1 17 17 53 53 102
18 236785 1 18 18 119 119 77
19 135473 1 19 19 41 41 82
20 202925 1 20 20 61 61 115
21 215147 1 21 21 58 58 101
22 344297 1 22 22 75 75 80
23 153935 1 23 23 33 33 50
24 132943 1 24 24 40 40 83
25 174724 1 25 25 92 92 123
26 174415 1 26 26 100 100 73
27 225548 1 27 27 112 112 81
28 223632 1 28 28 73 73 105
29 124817 1 29 29 40 40 47
30 221698 1 30 30 45 45 105
31 210767 1 31 31 60 60 94
32 170266 1 32 32 62 62 44
33 260561 1 33 33 75 75 114
34 84853 1 34 34 31 31 38
35 294424 1 35 35 77 77 107
36 215641 1 36 36 46 46 71
37 325107 1 37 37 99 99 84
38 167542 1 38 38 66 66 59
39 106408 1 39 39 30 30 33
40 265769 1 40 40 146 146 96
41 269651 1 41 41 67 67 106
42 149112 1 42 42 56 56 56
43 152871 1 43 43 58 58 59
44 111665 1 44 44 34 34 39
45 116408 1 45 45 61 61 34
46 362301 1 46 46 119 119 76
47 78800 1 47 47 42 42 20
48 183167 1 48 48 66 66 91
49 277965 1 49 49 89 89 115
50 150629 1 50 50 44 44 85
51 168809 1 51 51 66 66 76
52 24188 1 52 52 24 24 8
53 329267 1 53 53 259 259 79
54 65029 1 54 54 17 17 21
55 101097 1 55 55 64 64 30
56 218946 1 56 56 41 41 76
57 244052 1 57 57 68 68 101
58 233328 1 58 58 132 132 92
59 256462 1 59 59 105 105 123
60 206161 1 60 60 71 71 75
61 311473 1 61 61 112 112 128
62 235800 1 62 62 94 94 105
63 177939 1 63 63 82 82 55
64 207176 1 64 64 70 70 56
65 196553 1 65 65 57 57 41
66 174184 1 66 66 53 53 72
67 143246 1 67 67 103 103 67
68 187559 1 68 68 121 121 75
69 187681 1 69 69 62 62 114
70 119016 1 70 70 52 52 118
71 182192 1 71 71 52 52 77
72 73566 1 72 72 32 32 22
73 194979 1 73 73 62 62 66
74 167488 1 74 74 45 45 69
75 143756 1 75 75 46 46 105
76 275541 1 76 76 63 63 116
77 243199 1 77 77 75 75 88
78 182999 1 78 78 88 88 73
79 135649 1 79 79 46 46 99
80 152299 1 80 80 53 53 62
81 120221 1 81 81 37 37 53
82 346485 1 82 82 90 90 118
83 145790 1 83 83 63 63 30
84 193339 1 84 84 78 78 100
85 80953 1 85 85 25 25 49
86 122774 1 86 86 45 45 24
87 130585 1 87 87 46 46 67
88 286468 1 88 88 144 144 57
89 241066 1 89 89 82 82 75
90 148446 1 90 90 91 91 135
91 204713 1 91 91 71 71 68
92 182079 1 92 92 63 63 124
93 140344 1 93 93 53 53 33
94 220516 1 94 94 62 62 98
95 243060 1 95 95 63 63 58
96 162765 1 96 96 32 32 68
97 182613 1 97 97 39 39 81
98 232138 1 98 98 62 62 131
99 265318 1 99 99 117 117 110
100 310839 1 100 100 92 92 130
101 225060 1 101 101 93 93 93
102 232317 1 102 102 54 54 118
103 144966 1 103 103 144 144 39
104 43287 1 104 104 14 14 13
105 155754 1 105 105 61 61 74
106 164709 1 106 106 109 109 81
107 201940 1 107 107 38 38 109
108 235454 1 108 108 73 73 151
109 99466 1 109 109 50 50 28
110 100750 1 110 110 72 72 83
111 224549 1 111 111 50 50 54
112 243511 1 112 112 71 71 133
113 22938 1 113 113 10 10 12
114 152474 1 114 114 65 65 106
115 61857 1 115 115 25 25 23
116 132487 1 116 116 41 41 71
117 317394 1 117 117 86 86 116
118 21054 1 118 118 16 16 4
119 209641 1 119 119 42 42 62
120 31414 1 120 120 19 19 18
121 244749 1 121 121 95 95 98
122 184510 1 122 122 49 49 64
123 128423 1 123 123 64 64 32
124 97839 1 124 124 38 38 25
125 38214 1 125 125 34 34 16
126 151101 1 126 126 32 32 48
127 272458 1 127 127 65 65 100
128 172494 1 128 128 52 52 46
129 328107 1 129 129 65 65 129
130 250579 1 130 130 83 83 130
131 351067 1 131 131 95 95 136
132 158015 1 132 132 29 29 59
133 85439 1 133 133 33 33 32
134 229242 1 134 134 247 247 63
135 351619 1 135 135 139 139 95
136 84207 1 136 136 29 29 14
137 324598 1 137 137 110 110 113
138 131069 1 138 138 67 67 47
139 204271 1 139 139 42 42 92
140 165543 1 140 140 65 65 70
141 141722 1 141 141 94 94 19
142 299775 1 142 142 95 95 91
143 195838 1 143 143 67 67 111
144 173260 1 144 144 63 63 41
145 254488 1 145 145 83 83 120
146 104389 1 146 146 45 45 135
147 199476 1 147 147 70 70 87
148 224330 1 148 148 83 83 131
149 14688 1 149 149 10 10 4
150 181633 1 150 150 70 70 47
151 271856 1 151 151 103 103 109
152 7199 1 152 152 5 5 7
153 46660 1 153 153 20 20 12
154 17547 1 154 154 5 5 0
155 95227 1 155 155 34 34 37
156 152601 1 156 156 48 48 46
157 101645 0 157 0 63 0 20
158 101011 0 158 0 34 0 30
159 7176 0 159 0 17 0 0
160 96560 0 160 0 76 0 42
161 175824 0 161 0 107 0 57
162 341570 0 162 0 168 0 94
163 103597 0 163 0 43 0 27
164 112611 0 164 0 41 0 46
165 85574 0 165 0 34 0 37
166 220801 0 166 0 75 0 51
167 92661 0 167 0 61 0 40
168 133328 0 168 0 55 0 56
169 61361 0 169 0 77 0 27
170 125930 0 170 0 75 0 37
171 82316 0 171 0 32 0 27
172 102010 0 172 0 53 0 28
173 101523 0 173 0 42 0 59
174 41566 0 174 0 35 0 0
175 99923 0 175 0 66 0 44
176 22648 0 176 0 19 0 12
177 46698 0 177 0 45 0 14
178 131698 0 178 0 65 0 60
179 91735 0 179 0 35 0 7
180 79863 0 180 0 37 0 29
181 108043 0 181 0 62 0 45
182 98866 0 182 0 18 0 25
183 120445 0 183 0 118 0 36
184 116048 0 184 0 64 0 50
185 250047 0 185 0 81 0 41
186 136084 0 186 0 30 0 27
187 92499 0 187 0 32 0 25
188 135781 0 188 0 31 0 45
189 74408 0 189 0 67 0 29
190 81240 0 190 0 66 0 58
191 133368 0 191 0 36 0 37
192 98146 0 192 0 40 0 15
193 79619 0 193 0 43 0 42
194 59194 0 194 0 31 0 7
195 139942 0 195 0 42 0 54
196 118612 0 196 0 46 0 54
197 72880 0 197 0 33 0 14
198 65475 0 198 0 18 0 16
199 99643 0 199 0 55 0 33
200 71965 0 200 0 35 0 32
201 77272 0 201 0 59 0 21
202 49289 0 202 0 19 0 15
203 135131 0 203 0 66 0 38
204 108446 0 204 0 60 0 22
205 89746 0 205 0 36 0 28
206 44296 0 206 0 25 0 10
207 77648 0 207 0 47 0 31
208 181528 0 208 0 54 0 32
209 134019 0 209 0 53 0 32
210 124064 0 210 0 40 0 43
211 92630 0 211 0 40 0 27
212 121848 0 212 0 39 0 37
213 52915 0 213 0 14 0 20
214 81872 0 214 0 45 0 32
215 58981 0 215 0 36 0 0
216 53515 0 216 0 28 0 5
217 60812 0 217 0 44 0 26
218 56375 0 218 0 30 0 10
219 65490 0 219 0 22 0 27
220 80949 0 220 0 17 0 11
221 76302 0 221 0 31 0 29
222 104011 0 222 0 55 0 25
223 98104 0 223 0 54 0 55
224 67989 0 224 0 21 0 23
225 30989 0 225 0 14 0 5
226 135458 0 226 0 81 0 43
227 73504 0 227 0 35 0 23
228 63123 0 228 0 43 0 34
229 61254 0 229 0 46 0 36
230 74914 0 230 0 30 0 35
231 31774 0 231 0 23 0 0
232 81437 0 232 0 38 0 37
233 87186 0 233 0 54 0 28
234 50090 0 234 0 20 0 16
235 65745 0 235 0 53 0 26
236 56653 0 236 0 45 0 38
237 158399 0 237 0 39 0 23
238 46455 0 238 0 20 0 22
239 73624 0 239 0 24 0 30
240 38395 0 240 0 31 0 16
241 91899 0 241 0 35 0 18
242 139526 0 242 0 151 0 28
243 52164 0 243 0 52 0 32
244 51567 0 244 0 30 0 21
245 70551 0 245 0 31 0 23
246 84856 0 246 0 29 0 29
247 102538 0 247 0 57 0 50
248 86678 0 248 0 40 0 12
249 85709 0 249 0 44 0 21
250 34662 0 250 0 25 0 18
251 150580 0 251 0 77 0 27
252 99611 0 252 0 35 0 41
253 19349 0 253 0 11 0 13
254 99373 0 254 0 63 0 12
255 86230 0 255 0 44 0 21
256 30837 0 256 0 19 0 8
257 31706 0 257 0 13 0 26
258 89806 0 258 0 42 0 27
259 62088 0 259 0 38 0 13
260 40151 0 260 0 29 0 16
261 27634 0 261 0 20 0 2
262 76990 0 262 0 27 0 42
263 37460 0 263 0 20 0 5
264 54157 0 264 0 19 0 37
265 49862 0 265 0 37 0 17
266 84337 0 266 0 26 0 38
267 64175 0 267 0 42 0 37
268 59382 0 268 0 49 0 29
269 119308 0 269 0 30 0 32
270 76702 0 270 0 49 0 35
271 103425 0 271 0 67 0 17
272 70344 0 272 0 28 0 20
273 43410 0 273 0 19 0 7
274 104838 0 274 0 49 0 46
275 62215 0 275 0 27 0 24
276 69304 0 276 0 30 0 40
277 53117 0 277 0 22 0 3
278 19764 0 278 0 12 0 10
279 86680 0 279 0 31 0 37
280 84105 0 280 0 20 0 17
281 77945 0 281 0 20 0 28
282 89113 0 282 0 39 0 19
283 91005 0 283 0 29 0 29
284 40248 0 284 0 16 0 8
285 64187 0 285 0 27 0 10
286 50857 0 286 0 21 0 15
287 56613 0 287 0 19 0 15
288 62792 0 288 0 35 0 28
289 72535 0 289 0 14 0 17
Blogged_computations_P Compendiums_reviewed Compendiums_reviewed_P
1 79 30 30
2 58 28 28
3 60 38 38
4 108 30 30
5 49 22 22
6 0 26 26
7 121 25 25
8 1 18 18
9 43 26 26
10 69 25 25
11 78 38 38
12 86 44 44
13 44 30 30
14 104 40 40
15 63 34 34
16 158 47 47
17 102 30 30
18 77 31 31
19 82 23 23
20 115 36 36
21 101 36 36
22 80 30 30
23 50 25 25
24 83 39 39
25 123 34 34
26 73 31 31
27 81 31 31
28 105 33 33
29 47 25 25
30 105 33 33
31 94 35 35
32 44 42 42
33 114 43 43
34 38 30 30
35 107 33 33
36 71 32 32
37 84 36 36
38 59 28 28
39 33 14 14
40 96 32 32
41 106 30 30
42 56 35 35
43 59 28 28
44 39 28 28
45 34 39 39
46 76 34 34
47 20 26 26
48 91 39 39
49 115 39 39
50 85 33 33
51 76 28 28
52 8 4 4
53 79 39 39
54 21 18 18
55 30 14 14
56 76 29 29
57 101 44 44
58 92 28 28
59 123 35 35
60 75 28 28
61 128 38 38
62 105 23 23
63 55 36 36
64 56 32 32
65 41 29 29
66 72 25 25
67 67 27 27
68 75 36 36
69 114 28 28
70 118 23 23
71 77 40 40
72 22 23 23
73 66 40 40
74 69 28 28
75 105 34 34
76 116 33 33
77 88 28 28
78 73 34 34
79 99 30 30
80 62 33 33
81 53 22 22
82 118 38 38
83 30 26 26
84 100 35 35
85 49 8 8
86 24 24 24
87 67 29 29
88 57 29 29
89 75 45 45
90 135 37 37
91 68 33 33
92 124 33 33
93 33 25 25
94 98 32 32
95 58 29 29
96 68 28 28
97 81 28 28
98 131 31 31
99 110 52 52
100 130 24 24
101 93 41 41
102 118 33 33
103 39 32 32
104 13 19 19
105 74 20 20
106 81 31 31
107 109 31 31
108 151 32 32
109 28 23 23
110 83 30 30
111 54 31 31
112 133 42 42
113 12 1 1
114 106 32 32
115 23 11 11
116 71 36 36
117 116 31 31
118 4 0 0
119 62 24 24
120 18 8 8
121 98 33 33
122 64 40 40
123 32 38 38
124 25 24 24
125 16 8 8
126 48 35 35
127 100 43 43
128 46 43 43
129 129 41 41
130 130 38 38
131 136 45 45
132 59 31 31
133 32 28 28
134 63 31 31
135 95 40 40
136 14 30 30
137 113 37 37
138 47 30 30
139 92 35 35
140 70 32 32
141 19 27 27
142 91 31 31
143 111 31 31
144 41 21 21
145 120 39 39
146 135 41 41
147 87 32 32
148 131 39 39
149 4 0 0
150 47 30 30
151 109 37 37
152 7 0 0
153 12 5 5
154 0 1 1
155 37 32 32
156 46 24 24
157 0 11 0
158 0 13 0
159 0 0 0
160 0 17 0
161 0 20 0
162 0 21 0
163 0 16 0
164 0 20 0
165 0 21 0
166 0 18 0
167 0 17 0
168 0 20 0
169 0 12 0
170 0 17 0
171 0 10 0
172 0 13 0
173 0 22 0
174 0 9 0
175 0 25 0
176 0 13 0
177 0 13 0
178 0 19 0
179 0 18 0
180 0 22 0
181 0 14 0
182 0 13 0
183 0 16 0
184 0 20 0
185 0 18 0
186 0 13 0
187 0 18 0
188 0 14 0
189 0 7 0
190 0 17 0
191 0 16 0
192 0 17 0
193 0 11 0
194 0 24 0
195 0 22 0
196 0 12 0
197 0 19 0
198 0 13 0
199 0 17 0
200 0 15 0
201 0 16 0
202 0 24 0
203 0 15 0
204 0 17 0
205 0 18 0
206 0 20 0
207 0 16 0
208 0 16 0
209 0 18 0
210 0 22 0
211 0 8 0
212 0 17 0
213 0 18 0
214 0 16 0
215 0 23 0
216 0 22 0
217 0 13 0
218 0 13 0
219 0 16 0
220 0 16 0
221 0 20 0
222 0 22 0
223 0 17 0
224 0 18 0
225 0 17 0
226 0 12 0
227 0 7 0
228 0 17 0
229 0 14 0
230 0 23 0
231 0 17 0
232 0 14 0
233 0 15 0
234 0 17 0
235 0 21 0
236 0 18 0
237 0 18 0
238 0 17 0
239 0 17 0
240 0 16 0
241 0 15 0
242 0 21 0
243 0 16 0
244 0 14 0
245 0 15 0
246 0 17 0
247 0 15 0
248 0 15 0
249 0 10 0
250 0 6 0
251 0 22 0
252 0 21 0
253 0 1 0
254 0 18 0
255 0 17 0
256 0 4 0
257 0 10 0
258 0 16 0
259 0 16 0
260 0 9 0
261 0 16 0
262 0 17 0
263 0 7 0
264 0 15 0
265 0 14 0
266 0 14 0
267 0 18 0
268 0 12 0
269 0 16 0
270 0 21 0
271 0 19 0
272 0 16 0
273 0 1 0
274 0 16 0
275 0 10 0
276 0 19 0
277 0 12 0
278 0 2 0
279 0 14 0
280 0 17 0
281 0 19 0
282 0 14 0
283 0 11 0
284 0 4 0
285 0 16 0
286 0 20 0
287 0 12 0
288 0 15 0
289 0 16 0
Feedback_messages_p120 Feedback_messages_p120_P Total_number_of_characters
1 94 94 112285
2 103 103 84786
3 93 93 83123
4 103 103 101193
5 51 51 38361
6 70 70 68504
7 91 91 119182
8 22 22 22807
9 93 93 116174
10 60 60 57635
11 123 123 66198
12 148 148 71701
13 90 90 57793
14 124 124 80444
15 70 70 53855
16 168 168 97668
17 115 115 133824
18 71 71 101481
19 66 66 99645
20 134 134 114789
21 117 117 99052
22 108 108 67654
23 84 84 65553
24 156 156 97500
25 120 120 69112
26 114 114 82753
27 94 94 85323
28 120 120 72654
29 81 81 30727
30 110 110 77873
31 133 133 117478
32 122 122 74007
33 158 158 90183
34 109 109 61542
35 124 124 101494
36 92 92 55813
37 126 126 79215
38 70 70 55461
39 37 37 31081
40 120 120 83122
41 93 93 70106
42 95 95 60578
43 90 90 79892
44 80 80 49810
45 31 31 71570
46 110 110 100708
47 66 66 33032
48 138 138 82875
49 133 133 139077
50 113 113 71595
51 100 100 72260
52 7 7 5950
53 140 140 115762
54 61 61 32551
55 41 41 31701
56 96 96 80670
57 164 164 143558
58 102 102 120733
59 124 124 105195
60 99 99 73107
61 129 129 132068
62 62 62 149193
63 73 73 46821
64 114 114 87011
65 99 99 95260
66 70 70 55183
67 104 104 106671
68 116 116 73511
69 91 91 92945
70 74 74 78664
71 138 138 70054
72 67 67 22618
73 151 151 74011
74 72 72 83737
75 120 120 69094
76 115 115 93133
77 105 105 95536
78 104 104 225920
79 108 108 62133
80 98 98 61370
81 69 69 43836
82 111 111 106117
83 99 99 38692
84 71 71 84651
85 27 27 56622
86 69 69 15986
87 107 107 95364
88 107 107 89691
89 93 93 67267
90 129 129 126846
91 69 69 41140
92 118 118 102860
93 73 73 51715
94 119 119 55801
95 104 104 111813
96 107 107 120293
97 99 99 138599
98 90 90 161647
99 197 197 115929
100 85 85 162901
101 139 139 109825
102 106 106 129838
103 50 50 37510
104 64 64 43750
105 31 31 40652
106 63 63 87771
107 92 92 85872
108 106 106 89275
109 69 69 192565
110 93 93 140867
111 114 114 120662
112 110 110 101338
113 0 0 1168
114 83 83 65567
115 30 30 25162
116 98 98 40735
117 82 82 91413
118 0 0 855
119 60 60 97068
120 9 9 14116
121 115 115 76643
122 140 140 110681
123 120 120 92696
124 66 66 94785
125 21 21 8773
126 124 124 83209
127 152 152 93815
128 139 139 86687
129 144 144 105547
130 120 120 103487
131 160 160 213688
132 114 114 71220
133 78 78 56926
134 119 119 91721
135 141 141 115168
136 101 101 111194
137 133 133 135777
138 83 83 51513
139 116 116 74163
140 90 90 51633
141 36 36 75345
142 97 97 98952
143 98 98 102372
144 78 78 37238
145 117 117 103772
146 148 148 123969
147 105 105 135400
148 132 132 130115
149 0 0 6023
150 73 73 64466
151 86 86 54990
152 0 0 1644
153 13 13 6179
154 4 4 3926
155 48 48 34777
156 46 46 73224
157 38 0 17140
158 39 0 27570
159 0 0 1423
160 38 0 22996
161 77 0 39992
162 78 0 117105
163 49 0 23789
164 73 0 26706
165 36 0 24266
166 63 0 44418
167 41 0 35232
168 56 0 40909
169 25 0 13294
170 65 0 32387
171 38 0 21233
172 44 0 44332
173 87 0 61056
174 27 0 13497
175 80 0 32334
176 28 0 44339
177 33 0 10288
178 59 0 65622
179 49 0 16563
180 49 0 29011
181 38 0 34553
182 39 0 23517
183 56 0 51009
184 50 0 33416
185 61 0 83305
186 41 0 27142
187 55 0 21399
188 44 0 24874
189 21 0 34988
190 50 0 45549
191 57 0 32755
192 48 0 27114
193 32 0 20760
194 68 0 37636
195 87 0 65461
196 43 0 30080
197 67 0 24094
198 46 0 69008
199 46 0 54968
200 56 0 46090
201 48 0 27507
202 44 0 10672
203 60 0 34029
204 65 0 46300
205 55 0 24760
206 38 0 18779
207 52 0 21280
208 60 0 40662
209 54 0 28987
210 86 0 22827
211 24 0 18513
212 52 0 30594
213 49 0 24006
214 61 0 27913
215 61 0 42744
216 81 0 12934
217 43 0 22574
218 40 0 41385
219 40 0 18653
220 56 0 18472
221 68 0 30976
222 79 0 63339
223 47 0 25568
224 57 0 33747
225 41 0 4154
226 29 0 19474
227 3 0 35130
228 60 0 39067
229 30 0 13310
230 79 0 65892
231 47 0 4143
232 40 0 28579
233 48 0 51776
234 36 0 21152
235 42 0 38084
236 49 0 27717
237 57 0 32928
238 12 0 11342
239 40 0 19499
240 43 0 16380
241 33 0 36874
242 77 0 48259
243 43 0 16734
244 45 0 28207
245 47 0 30143
246 43 0 41369
247 45 0 45833
248 50 0 29156
249 35 0 35944
250 7 0 36278
251 71 0 45588
252 67 0 45097
253 0 0 3895
254 62 0 28394
255 54 0 18632
256 4 0 2325
257 25 0 25139
258 40 0 27975
259 38 0 14483
260 19 0 13127
261 17 0 5839
262 67 0 24069
263 14 0 3738
264 30 0 18625
265 54 0 36341
266 35 0 24548
267 59 0 21792
268 24 0 26263
269 58 0 23686
270 42 0 49303
271 46 0 25659
272 61 0 28904
273 3 0 2781
274 52 0 29236
275 25 0 19546
276 40 0 22818
277 32 0 32689
278 4 0 5752
279 49 0 22197
280 63 0 20055
281 67 0 25272
282 32 0 82206
283 23 0 32073
284 7 0 5444
285 54 0 20154
286 37 0 36944
287 35 0 8019
288 51 0 30884
289 39 0 19540
Total_number_of_characters_P
1 112285
2 84786
3 83123
4 101193
5 38361
6 68504
7 119182
8 22807
9 116174
10 57635
11 66198
12 71701
13 57793
14 80444
15 53855
16 97668
17 133824
18 101481
19 99645
20 114789
21 99052
22 67654
23 65553
24 97500
25 69112
26 82753
27 85323
28 72654
29 30727
30 77873
31 117478
32 74007
33 90183
34 61542
35 101494
36 55813
37 79215
38 55461
39 31081
40 83122
41 70106
42 60578
43 79892
44 49810
45 71570
46 100708
47 33032
48 82875
49 139077
50 71595
51 72260
52 5950
53 115762
54 32551
55 31701
56 80670
57 143558
58 120733
59 105195
60 73107
61 132068
62 149193
63 46821
64 87011
65 95260
66 55183
67 106671
68 73511
69 92945
70 78664
71 70054
72 22618
73 74011
74 83737
75 69094
76 93133
77 95536
78 225920
79 62133
80 61370
81 43836
82 106117
83 38692
84 84651
85 56622
86 15986
87 95364
88 89691
89 67267
90 126846
91 41140
92 102860
93 51715
94 55801
95 111813
96 120293
97 138599
98 161647
99 115929
100 162901
101 109825
102 129838
103 37510
104 43750
105 40652
106 87771
107 85872
108 89275
109 192565
110 140867
111 120662
112 101338
113 1168
114 65567
115 25162
116 40735
117 91413
118 855
119 97068
120 14116
121 76643
122 110681
123 92696
124 94785
125 8773
126 83209
127 93815
128 86687
129 105547
130 103487
131 213688
132 71220
133 56926
134 91721
135 115168
136 111194
137 135777
138 51513
139 74163
140 51633
141 75345
142 98952
143 102372
144 37238
145 103772
146 123969
147 135400
148 130115
149 6023
150 64466
151 54990
152 1644
153 6179
154 3926
155 34777
156 73224
157 0
158 0
159 0
160 0
161 0
162 0
163 0
164 0
165 0
166 0
167 0
168 0
169 0
170 0
171 0
172 0
173 0
174 0
175 0
176 0
177 0
178 0
179 0
180 0
181 0
182 0
183 0
184 0
185 0
186 0
187 0
188 0
189 0
190 0
191 0
192 0
193 0
194 0
195 0
196 0
197 0
198 0
199 0
200 0
201 0
202 0
203 0
204 0
205 0
206 0
207 0
208 0
209 0
210 0
211 0
212 0
213 0
214 0
215 0
216 0
217 0
218 0
219 0
220 0
221 0
222 0
223 0
224 0
225 0
226 0
227 0
228 0
229 0
230 0
231 0
232 0
233 0
234 0
235 0
236 0
237 0
238 0
239 0
240 0
241 0
242 0
243 0
244 0
245 0
246 0
247 0
248 0
249 0
250 0
251 0
252 0
253 0
254 0
255 0
256 0
257 0
258 0
259 0
260 0
261 0
262 0
263 0
264 0
265 0
266 0
267 0
268 0
269 0
270 0
271 0
272 0
273 0
274 0
275 0
276 0
277 0
278 0
279 0
280 0
281 0
282 0
283 0
284 0
285 0
286 0
287 0
288 0
289 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pop
2.874e+04 -1.491e+04
T Pop_t
-7.454e+01 1.573e+01
Logins Logins_P
6.324e+02 1.285e+02
Blogged_computations Blogged_computations_P
8.352e+02 9.283e+01
Compendiums_reviewed Compendiums_reviewed_P
-1.360e+03 2.241e+03
Feedback_messages_p120 Feedback_messages_p120_P
6.603e+02 -5.147e+02
Total_number_of_characters Total_number_of_characters_P
5.061e-01 -3.212e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-140943 -18317 -2770 14839 145809
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.874e+04 2.614e+04 1.099 0.272529
Pop -1.491e+04 2.864e+04 -0.521 0.603017
T -7.454e+01 9.120e+01 -0.817 0.414462
Pop_t 1.573e+01 1.129e+02 0.139 0.889258
Logins 6.324e+02 1.786e+02 3.541 0.000468 ***
Logins_P 1.285e+02 2.020e+02 0.636 0.525254
Blogged_computations 8.352e+02 2.750e+02 3.037 0.002622 **
Blogged_computations_P 9.283e+01 2.992e+02 0.310 0.756632
Compendiums_reviewed -1.360e+03 1.160e+03 -1.173 0.241968
Compendiums_reviewed_P 2.241e+03 1.327e+03 1.688 0.092518 .
Feedback_messages_p120 6.603e+02 3.155e+02 2.093 0.037260 *
Feedback_messages_p120_P -5.147e+02 3.597e+02 -1.431 0.153596
Total_number_of_characters 5.061e-01 2.432e-01 2.081 0.038352 *
Total_number_of_characters_P -3.212e-01 2.639e-01 -1.217 0.224528
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36760 on 275 degrees of freedom
Multiple R-squared: 0.8096, Adjusted R-squared: 0.8006
F-statistic: 89.97 on 13 and 275 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.9977721 4.455861e-03 2.227931e-03
[2,] 0.9950586 9.882832e-03 4.941416e-03
[3,] 0.9980184 3.963204e-03 1.981602e-03
[4,] 0.9967827 6.434634e-03 3.217317e-03
[5,] 0.9935415 1.291708e-02 6.458538e-03
[6,] 0.9999844 3.123422e-05 1.561711e-05
[7,] 0.9999647 7.058092e-05 3.529046e-05
[8,] 0.9999621 7.578474e-05 3.789237e-05
[9,] 0.9999966 6.872482e-06 3.436241e-06
[10,] 0.9999952 9.536271e-06 4.768135e-06
[11,] 0.9999898 2.036130e-05 1.018065e-05
[12,] 0.9999793 4.141748e-05 2.070874e-05
[13,] 0.9999596 8.070262e-05 4.035131e-05
[14,] 0.9999300 1.399655e-04 6.998274e-05
[15,] 0.9998718 2.563755e-04 1.281877e-04
[16,] 0.9998247 3.506198e-04 1.753099e-04
[17,] 0.9997366 5.268944e-04 2.634472e-04
[18,] 0.9996406 7.187761e-04 3.593880e-04
[19,] 0.9997081 5.837054e-04 2.918527e-04
[20,] 0.9996880 6.239825e-04 3.119913e-04
[21,] 0.9999431 1.138626e-04 5.693129e-05
[22,] 0.9999195 1.610535e-04 8.052675e-05
[23,] 0.9998774 2.451646e-04 1.225823e-04
[24,] 0.9998247 3.505184e-04 1.752592e-04
[25,] 0.9997920 4.160893e-04 2.080446e-04
[26,] 0.9997157 5.686079e-04 2.843039e-04
[27,] 0.9996224 7.551000e-04 3.775500e-04
[28,] 0.9994420 1.116049e-03 5.580244e-04
[29,] 0.9993773 1.245375e-03 6.226876e-04
[30,] 0.9999636 7.284126e-05 3.642063e-05
[31,] 0.9999514 9.720742e-05 4.860371e-05
[32,] 0.9999432 1.135744e-04 5.678721e-05
[33,] 0.9999155 1.690142e-04 8.450711e-05
[34,] 0.9999036 1.928363e-04 9.641816e-05
[35,] 0.9998793 2.414570e-04 1.207285e-04
[36,] 0.9998703 2.593879e-04 1.296940e-04
[37,] 0.9998764 2.471095e-04 1.235548e-04
[38,] 0.9998116 3.767557e-04 1.883778e-04
[39,] 0.9997345 5.309578e-04 2.654789e-04
[40,] 0.9997592 4.816814e-04 2.408407e-04
[41,] 0.9996417 7.166150e-04 3.583075e-04
[42,] 0.9996460 7.079664e-04 3.539832e-04
[43,] 0.9995722 8.555495e-04 4.277747e-04
[44,] 0.9994200 1.160024e-03 5.800121e-04
[45,] 0.9992157 1.568535e-03 7.842673e-04
[46,] 0.9991087 1.782548e-03 8.912740e-04
[47,] 0.9987361 2.527858e-03 1.263929e-03
[48,] 0.9986405 2.718966e-03 1.359483e-03
[49,] 0.9988628 2.274414e-03 1.137207e-03
[50,] 0.9984841 3.031885e-03 1.515942e-03
[51,] 0.9991799 1.640269e-03 8.201343e-04
[52,] 0.9991931 1.613892e-03 8.069460e-04
[53,] 0.9991972 1.605624e-03 8.028118e-04
[54,] 0.9998042 3.915431e-04 1.957715e-04
[55,] 0.9997166 5.668635e-04 2.834317e-04
[56,] 0.9995985 8.029083e-04 4.014542e-04
[57,] 0.9994546 1.090708e-03 5.453542e-04
[58,] 0.9992504 1.499226e-03 7.496131e-04
[59,] 0.9994256 1.148748e-03 5.743741e-04
[60,] 0.9995394 9.212057e-04 4.606028e-04
[61,] 0.9995406 9.188886e-04 4.594443e-04
[62,] 0.9996145 7.710227e-04 3.855113e-04
[63,] 0.9996877 6.246094e-04 3.123047e-04
[64,] 0.9995612 8.776504e-04 4.388252e-04
[65,] 0.9993845 1.230969e-03 6.154847e-04
[66,] 0.9998759 2.481035e-04 1.240518e-04
[67,] 0.9998434 3.132566e-04 1.566283e-04
[68,] 0.9998023 3.954544e-04 1.977272e-04
[69,] 0.9997252 5.495781e-04 2.747891e-04
[70,] 0.9996768 6.464644e-04 3.232322e-04
[71,] 0.9996235 7.530927e-04 3.765464e-04
[72,] 0.9997816 4.367989e-04 2.183994e-04
[73,] 0.9997807 4.386736e-04 2.193368e-04
[74,] 0.9999939 1.229351e-05 6.146757e-06
[75,] 0.9999938 1.230833e-05 6.154167e-06
[76,] 0.9999954 9.219282e-06 4.609641e-06
[77,] 0.9999941 1.182621e-05 5.913105e-06
[78,] 0.9999922 1.553492e-05 7.767458e-06
[79,] 0.9999979 4.151382e-06 2.075691e-06
[80,] 0.9999969 6.211179e-06 3.105589e-06
[81,] 0.9999954 9.237304e-06 4.618652e-06
[82,] 0.9999932 1.353399e-05 6.766995e-06
[83,] 0.9999912 1.752360e-05 8.761798e-06
[84,] 0.9999939 1.225705e-05 6.128523e-06
[85,] 0.9999911 1.786332e-05 8.931660e-06
[86,] 0.9999871 2.582759e-05 1.291379e-05
[87,] 0.9999889 2.220906e-05 1.110453e-05
[88,] 0.9999847 3.050929e-05 1.525464e-05
[89,] 0.9999784 4.318669e-05 2.159335e-05
[90,] 0.9999820 3.600636e-05 1.800318e-05
[91,] 0.9999746 5.074526e-05 2.537263e-05
[92,] 0.9999685 6.302941e-05 3.151471e-05
[93,] 0.9999651 6.973163e-05 3.486582e-05
[94,] 0.9999981 3.806592e-06 1.903296e-06
[95,] 0.9999991 1.858490e-06 9.292450e-07
[96,] 0.9999988 2.439976e-06 1.219988e-06
[97,] 0.9999981 3.718369e-06 1.859185e-06
[98,] 0.9999993 1.480750e-06 7.403752e-07
[99,] 0.9999989 2.156699e-06 1.078350e-06
[100,] 0.9999989 2.136961e-06 1.068481e-06
[101,] 0.9999996 7.515075e-07 3.757538e-07
[102,] 0.9999994 1.145599e-06 5.727993e-07
[103,] 0.9999997 5.822443e-07 2.911221e-07
[104,] 0.9999996 7.518635e-07 3.759317e-07
[105,] 0.9999994 1.114661e-06 5.573304e-07
[106,] 0.9999992 1.693044e-06 8.465222e-07
[107,] 0.9999990 2.041685e-06 1.020842e-06
[108,] 0.9999987 2.694592e-06 1.347296e-06
[109,] 0.9999990 2.067706e-06 1.033853e-06
[110,] 0.9999985 2.997043e-06 1.498522e-06
[111,] 0.9999987 2.674982e-06 1.337491e-06
[112,] 0.9999980 3.961766e-06 1.980883e-06
[113,] 0.9999994 1.269829e-06 6.349146e-07
[114,] 0.9999992 1.503557e-06 7.517785e-07
[115,] 0.9999992 1.502004e-06 7.510018e-07
[116,] 0.9999990 1.995658e-06 9.978292e-07
[117,] 0.9999989 2.122227e-06 1.061114e-06
[118,] 1.0000000 9.418984e-10 4.709492e-10
[119,] 1.0000000 6.404253e-10 3.202127e-10
[120,] 1.0000000 9.742030e-10 4.871015e-10
[121,] 1.0000000 8.747764e-10 4.373882e-10
[122,] 1.0000000 8.965096e-10 4.482548e-10
[123,] 1.0000000 1.599740e-10 7.998698e-11
[124,] 1.0000000 2.545330e-10 1.272665e-10
[125,] 1.0000000 1.837395e-11 9.186975e-12
[126,] 1.0000000 1.258321e-11 6.291604e-12
[127,] 1.0000000 2.076123e-11 1.038061e-11
[128,] 1.0000000 2.500643e-11 1.250322e-11
[129,] 1.0000000 2.817463e-11 1.408731e-11
[130,] 1.0000000 3.140700e-12 1.570350e-12
[131,] 1.0000000 5.879360e-12 2.939680e-12
[132,] 1.0000000 8.874822e-12 4.437411e-12
[133,] 1.0000000 1.648861e-11 8.244305e-12
[134,] 1.0000000 2.684573e-11 1.342286e-11
[135,] 1.0000000 4.340751e-11 2.170375e-11
[136,] 1.0000000 7.957362e-11 3.978681e-11
[137,] 1.0000000 1.440217e-10 7.201084e-11
[138,] 1.0000000 2.597069e-10 1.298534e-10
[139,] 1.0000000 4.623115e-10 2.311557e-10
[140,] 1.0000000 7.584937e-10 3.792469e-10
[141,] 1.0000000 1.299573e-09 6.497864e-10
[142,] 1.0000000 2.069069e-09 1.034535e-09
[143,] 1.0000000 3.039774e-09 1.519887e-09
[144,] 1.0000000 4.717045e-09 2.358523e-09
[145,] 1.0000000 8.190106e-09 4.095053e-09
[146,] 1.0000000 1.944218e-09 9.721090e-10
[147,] 1.0000000 3.182688e-09 1.591344e-09
[148,] 1.0000000 5.563719e-09 2.781859e-09
[149,] 1.0000000 9.343692e-09 4.671846e-09
[150,] 1.0000000 6.162939e-10 3.081469e-10
[151,] 1.0000000 8.916705e-10 4.458352e-10
[152,] 1.0000000 1.473635e-09 7.368174e-10
[153,] 1.0000000 1.762704e-09 8.813519e-10
[154,] 1.0000000 3.040571e-09 1.520285e-09
[155,] 1.0000000 5.387358e-09 2.693679e-09
[156,] 1.0000000 9.068830e-09 4.534415e-09
[157,] 1.0000000 4.963595e-09 2.481797e-09
[158,] 1.0000000 7.930306e-09 3.965153e-09
[159,] 1.0000000 9.963930e-09 4.981965e-09
[160,] 1.0000000 7.218092e-09 3.609046e-09
[161,] 1.0000000 9.343295e-09 4.671648e-09
[162,] 1.0000000 1.495283e-08 7.476416e-09
[163,] 1.0000000 1.581427e-08 7.907133e-09
[164,] 1.0000000 2.698369e-08 1.349185e-08
[165,] 1.0000000 4.456531e-08 2.228266e-08
[166,] 1.0000000 4.513334e-08 2.256667e-08
[167,] 1.0000000 4.049119e-08 2.024559e-08
[168,] 1.0000000 6.963691e-08 3.481846e-08
[169,] 1.0000000 2.392543e-10 1.196271e-10
[170,] 1.0000000 4.157260e-11 2.078630e-11
[171,] 1.0000000 7.279124e-11 3.639562e-11
[172,] 1.0000000 3.012620e-11 1.506310e-11
[173,] 1.0000000 4.044366e-11 2.022183e-11
[174,] 1.0000000 1.386058e-11 6.930289e-12
[175,] 1.0000000 9.087253e-12 4.543627e-12
[176,] 1.0000000 1.123982e-11 5.619911e-12
[177,] 1.0000000 2.154394e-11 1.077197e-11
[178,] 1.0000000 3.840359e-11 1.920179e-11
[179,] 1.0000000 6.863457e-11 3.431728e-11
[180,] 1.0000000 1.246521e-10 6.232605e-11
[181,] 1.0000000 2.474164e-10 1.237082e-10
[182,] 1.0000000 4.228719e-10 2.114360e-10
[183,] 1.0000000 8.287831e-10 4.143916e-10
[184,] 1.0000000 1.053438e-09 5.267190e-10
[185,] 1.0000000 1.781110e-09 8.905552e-10
[186,] 1.0000000 3.332793e-09 1.666397e-09
[187,] 1.0000000 5.148105e-09 2.574052e-09
[188,] 1.0000000 9.901309e-09 4.950654e-09
[189,] 1.0000000 1.809049e-08 9.045244e-09
[190,] 1.0000000 3.353836e-08 1.676918e-08
[191,] 1.0000000 5.608267e-08 2.804133e-08
[192,] 1.0000000 9.841624e-10 4.920812e-10
[193,] 1.0000000 4.137997e-10 2.068999e-10
[194,] 1.0000000 5.445266e-10 2.722633e-10
[195,] 1.0000000 5.822719e-10 2.911360e-10
[196,] 1.0000000 2.544733e-10 1.272366e-10
[197,] 1.0000000 5.431568e-10 2.715784e-10
[198,] 1.0000000 1.097220e-09 5.486100e-10
[199,] 1.0000000 2.210814e-09 1.105407e-09
[200,] 1.0000000 3.996234e-09 1.998117e-09
[201,] 1.0000000 6.861825e-09 3.430912e-09
[202,] 1.0000000 1.354524e-08 6.772619e-09
[203,] 1.0000000 2.634030e-08 1.317015e-08
[204,] 1.0000000 2.756290e-08 1.378145e-08
[205,] 1.0000000 5.490996e-08 2.745498e-08
[206,] 0.9999999 1.066776e-07 5.333880e-08
[207,] 0.9999999 2.076561e-07 1.038280e-07
[208,] 0.9999998 4.049878e-07 2.024939e-07
[209,] 0.9999996 7.636330e-07 3.818165e-07
[210,] 0.9999998 3.567719e-07 1.783860e-07
[211,] 0.9999998 4.125385e-07 2.062693e-07
[212,] 0.9999998 4.620264e-07 2.310132e-07
[213,] 0.9999996 8.994922e-07 4.497461e-07
[214,] 0.9999996 7.423183e-07 3.711592e-07
[215,] 0.9999995 1.068202e-06 5.341011e-07
[216,] 0.9999990 2.057594e-06 1.028797e-06
[217,] 0.9999981 3.808654e-06 1.904327e-06
[218,] 0.9999964 7.135583e-06 3.567792e-06
[219,] 0.9999948 1.038763e-05 5.193813e-06
[220,] 0.9999954 9.252140e-06 4.626070e-06
[221,] 1.0000000 6.451064e-08 3.225532e-08
[222,] 0.9999999 1.340147e-07 6.700735e-08
[223,] 0.9999999 2.434120e-07 1.217060e-07
[224,] 0.9999998 3.052808e-07 1.526404e-07
[225,] 0.9999999 2.535122e-07 1.267561e-07
[226,] 0.9999999 1.899564e-07 9.497818e-08
[227,] 0.9999999 1.133005e-07 5.665023e-08
[228,] 0.9999999 1.887918e-07 9.439592e-08
[229,] 0.9999998 4.660822e-07 2.330411e-07
[230,] 0.9999996 7.985294e-07 3.992647e-07
[231,] 0.9999990 1.908290e-06 9.541451e-07
[232,] 0.9999982 3.678434e-06 1.839217e-06
[233,] 0.9999963 7.418071e-06 3.709036e-06
[234,] 0.9999919 1.610114e-05 8.050571e-06
[235,] 0.9999946 1.073131e-05 5.365656e-06
[236,] 0.9999895 2.106258e-05 1.053129e-05
[237,] 0.9999755 4.892544e-05 2.446272e-05
[238,] 0.9999499 1.002794e-04 5.013971e-05
[239,] 0.9999075 1.849078e-04 9.245388e-05
[240,] 0.9997987 4.026564e-04 2.013282e-04
[241,] 0.9996514 6.972881e-04 3.486441e-04
[242,] 0.9995153 9.693385e-04 4.846693e-04
[243,] 0.9990176 1.964709e-03 9.823544e-04
[244,] 0.9979964 4.007108e-03 2.003554e-03
[245,] 0.9959176 8.164837e-03 4.082419e-03
[246,] 0.9923076 1.538481e-02 7.692405e-03
[247,] 0.9855855 2.882906e-02 1.441453e-02
[248,] 0.9740234 5.195322e-02 2.597661e-02
[249,] 0.9727807 5.443853e-02 2.721927e-02
[250,] 0.9553595 8.928104e-02 4.464052e-02
[251,] 0.9547741 9.045178e-02 4.522589e-02
[252,] 0.9350796 1.298409e-01 6.492043e-02
[253,] 0.9533621 9.327582e-02 4.663791e-02
[254,] 0.9212451 1.575099e-01 7.875495e-02
[255,] 0.8576594 2.846813e-01 1.423406e-01
[256,] 0.7331228 5.337544e-01 2.668772e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1exw11323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2u5k41323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3yfl41323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4xk071323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5166e1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5
20354.31101 -44488.12297 3719.15459 -62335.24750 -148.97617
6 7 8 9 10
-25502.93817 132531.04483 -18085.04372 4467.06262 21656.50433
11 12 13 14 15
24127.59773 -60107.54490 -12817.97456 35554.93488 8366.12334
16 17 18 19 20
-35786.18694 15251.84694 5619.29785 -32816.70385 -35291.70092
21 22 23 24 25
-2352.50021 145808.63248 23586.00784 -62011.14785 -81966.05035
26 27 28 29 30
-40908.01894 -3834.93329 -1495.25631 -846.09616 18482.41975
31 32 33 34 35
-6024.21642 1886.75957 8276.90486 -39490.89054 58895.24659
36 37 38 39 40
51149.04463 95487.99097 5876.54405 17958.59703 -6896.14006
41 42 43 44 45
55967.59211 -12674.27234 -9840.93440 -7150.72298 -24829.37116
46 47 48 49 50
125535.17057 -21392.94355 -32258.47834 13163.93870 -31364.87975
51 52 53 54 55
-15340.22014 -17913.01979 -27940.91442 -8797.95560 -10192.66940
56 57 58 59 60
52258.63519 -1051.48196 -24725.69809 -16252.77860 19653.85262
61 62 63 64 65
20572.36971 -207.88316 3398.36601 31021.74756 47568.85201
66 67 68 69 70
14684.85135 -65824.07218 -46113.23293 -30145.75625 -85338.48905
71 72 73 74 75
-6747.03318 -14982.92296 6134.06359 9118.57421 -58287.01294
76 77 78 79 80
47578.38570 37564.18407 -47789.23968 -54034.88373 -9360.04375
81 82 83 84 85
-3704.90591 90255.35014 16607.14188 -24506.70424 -13818.29789
86 87 88 89 90
23355.79571 -34048.52078 57660.08995 34877.82348 -129421.79281
91 92 93 94 95
32397.98203 -54601.76027 18830.55055 18277.34064 71710.70698
96 97 98 99 100
4656.51087 4953.10149 -14956.90403 -29688.71412 48624.57912
101 102 103 104 105
-16536.24252 5399.17628 -50954.74810 -21280.23837 3370.85240
106 107 108 109 110
-53686.39445 7768.57031 -27812.67002 -37879.09924 -104416.40689
111 112 113 114 115
62891.25590 -12912.29012 -4091.45542 -54861.35779 -4283.58241
116 117 118 119 120
-25104.17968 81225.13093 -1883.71483 65501.09984 -17487.21729
121 122 123 124 125
14839.01738 5115.50768 -24631.40670 -9077.39332 -20708.39322
126 127 128 129 130
11534.82127 46504.63513 9813.93194 76114.87432 -9461.96886
131 132 133 134 135
44028.30456 18069.94619 -21910.06408 -84678.29933 74769.34700
136 137 138 139 140
-18358.60217 53221.84025 -17263.26914 19864.04314 -5296.89235
141 142 143 144 145
4084.69626 77852.89074 -24060.25778 45184.17555 4112.84198
146 147 148 149 150
-140942.56072 -8201.88223 -43130.13321 -2816.98585 30784.69957
151 152 153 154 155
32116.33323 -8299.92624 8033.78636 6777.32192 -11290.90673
156 157 158 159 160
27366.05699 9257.04231 15465.12192 -21185.85863 -17003.40718
161 162 163 164 165
-67.44757 57953.02609 14628.78481 -2769.77288 9235.64174
166 167 168 169 170
74812.83975 -17397.83892 5077.38828 -32942.16090 -4659.17680
171 172 173 174 175
1296.87281 -4620.43671 -48583.89365 -8758.10844 -29446.55405
176 177 178 179 180
-38260.27712 -18316.87619 -21318.45870 32099.01134 -197.41986
181 182 183 184 185
-7535.99743 31453.83130 -40372.39380 -3936.39313 91674.56454
186 187 188 189 190
56556.36880 13913.78512 41263.23651 -28888.17358 -56463.25937
191 192 193 194 195
32741.89978 23596.56892 -13683.30971 -11844.13686 -6578.13190
196 197 198 199 200
2994.31556 -4331.97509 -20870.56016 -11678.83263 -30629.77031
201 202 203 204 205
-15191.28980 9245.47919 11608.19225 -4636.16253 5766.64234
206 207 208 209 210
-648.12621 -14621.73170 68980.60731 34768.15792 11349.48024
211 212 213 214 215
17434.07082 26645.05345 -5531.46348 -18745.51815 -7130.07907
216 217 218 219 220
-11118.43158 -23431.43325 -13116.29909 2516.99865 24102.94805
221 222 223 224 225
-13167.41281 -18140.11030 -14953.22079 -6781.22634 -66.40701
226 227 228 229 230
23742.48012 10099.83407 -40481.02481 -17080.21435 -39116.09077
231 232 233 234 235
-4305.32299 -6779.63091 -19218.07931 1423.44661 -19157.17278
236 237 238 239 240
-36593.62699 73629.93575 13886.18000 9303.29753 -20347.05591
241 242 243 244 245
23903.26613 -36753.74286 -33176.27828 -20446.08614 -4630.64885
246 247 248 249 250
5682.26255 -18105.81032 13734.76252 2463.30507 -21110.09935
251 252 253 254 255
29273.58266 -5225.36905 -8960.60088 8875.09866 9166.80623
256 257 258 259 260
4101.44915 -23445.87532 12375.60503 7102.70755 -7862.37908
261 262 263 264 265
11607.34998 -17675.65689 9881.54942 -6659.74271 -31730.01955
266 267 268 269 270
10749.04020 -27632.85392 -17408.91446 36395.43933 -16256.13556
271 272 273 274 275
20797.10493 -5679.15563 15126.60058 -256.45944 4052.73283
276 277 278 279 280
-3364.61545 7251.78743 -7029.69052 3680.53941 20760.10145
281 282 283 284 285
2926.04372 -2831.39672 24339.39886 13937.47214 7167.16670
286 287 288 289
1697.29167 13871.40964 -18905.86587 28402.17160
> postscript(file="/var/wessaorg/rcomp/tmp/6kqbn1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 20354.31101 NA
1 -44488.12297 20354.31101
2 3719.15459 -44488.12297
3 -62335.24750 3719.15459
4 -148.97617 -62335.24750
5 -25502.93817 -148.97617
6 132531.04483 -25502.93817
7 -18085.04372 132531.04483
8 4467.06262 -18085.04372
9 21656.50433 4467.06262
10 24127.59773 21656.50433
11 -60107.54490 24127.59773
12 -12817.97456 -60107.54490
13 35554.93488 -12817.97456
14 8366.12334 35554.93488
15 -35786.18694 8366.12334
16 15251.84694 -35786.18694
17 5619.29785 15251.84694
18 -32816.70385 5619.29785
19 -35291.70092 -32816.70385
20 -2352.50021 -35291.70092
21 145808.63248 -2352.50021
22 23586.00784 145808.63248
23 -62011.14785 23586.00784
24 -81966.05035 -62011.14785
25 -40908.01894 -81966.05035
26 -3834.93329 -40908.01894
27 -1495.25631 -3834.93329
28 -846.09616 -1495.25631
29 18482.41975 -846.09616
30 -6024.21642 18482.41975
31 1886.75957 -6024.21642
32 8276.90486 1886.75957
33 -39490.89054 8276.90486
34 58895.24659 -39490.89054
35 51149.04463 58895.24659
36 95487.99097 51149.04463
37 5876.54405 95487.99097
38 17958.59703 5876.54405
39 -6896.14006 17958.59703
40 55967.59211 -6896.14006
41 -12674.27234 55967.59211
42 -9840.93440 -12674.27234
43 -7150.72298 -9840.93440
44 -24829.37116 -7150.72298
45 125535.17057 -24829.37116
46 -21392.94355 125535.17057
47 -32258.47834 -21392.94355
48 13163.93870 -32258.47834
49 -31364.87975 13163.93870
50 -15340.22014 -31364.87975
51 -17913.01979 -15340.22014
52 -27940.91442 -17913.01979
53 -8797.95560 -27940.91442
54 -10192.66940 -8797.95560
55 52258.63519 -10192.66940
56 -1051.48196 52258.63519
57 -24725.69809 -1051.48196
58 -16252.77860 -24725.69809
59 19653.85262 -16252.77860
60 20572.36971 19653.85262
61 -207.88316 20572.36971
62 3398.36601 -207.88316
63 31021.74756 3398.36601
64 47568.85201 31021.74756
65 14684.85135 47568.85201
66 -65824.07218 14684.85135
67 -46113.23293 -65824.07218
68 -30145.75625 -46113.23293
69 -85338.48905 -30145.75625
70 -6747.03318 -85338.48905
71 -14982.92296 -6747.03318
72 6134.06359 -14982.92296
73 9118.57421 6134.06359
74 -58287.01294 9118.57421
75 47578.38570 -58287.01294
76 37564.18407 47578.38570
77 -47789.23968 37564.18407
78 -54034.88373 -47789.23968
79 -9360.04375 -54034.88373
80 -3704.90591 -9360.04375
81 90255.35014 -3704.90591
82 16607.14188 90255.35014
83 -24506.70424 16607.14188
84 -13818.29789 -24506.70424
85 23355.79571 -13818.29789
86 -34048.52078 23355.79571
87 57660.08995 -34048.52078
88 34877.82348 57660.08995
89 -129421.79281 34877.82348
90 32397.98203 -129421.79281
91 -54601.76027 32397.98203
92 18830.55055 -54601.76027
93 18277.34064 18830.55055
94 71710.70698 18277.34064
95 4656.51087 71710.70698
96 4953.10149 4656.51087
97 -14956.90403 4953.10149
98 -29688.71412 -14956.90403
99 48624.57912 -29688.71412
100 -16536.24252 48624.57912
101 5399.17628 -16536.24252
102 -50954.74810 5399.17628
103 -21280.23837 -50954.74810
104 3370.85240 -21280.23837
105 -53686.39445 3370.85240
106 7768.57031 -53686.39445
107 -27812.67002 7768.57031
108 -37879.09924 -27812.67002
109 -104416.40689 -37879.09924
110 62891.25590 -104416.40689
111 -12912.29012 62891.25590
112 -4091.45542 -12912.29012
113 -54861.35779 -4091.45542
114 -4283.58241 -54861.35779
115 -25104.17968 -4283.58241
116 81225.13093 -25104.17968
117 -1883.71483 81225.13093
118 65501.09984 -1883.71483
119 -17487.21729 65501.09984
120 14839.01738 -17487.21729
121 5115.50768 14839.01738
122 -24631.40670 5115.50768
123 -9077.39332 -24631.40670
124 -20708.39322 -9077.39332
125 11534.82127 -20708.39322
126 46504.63513 11534.82127
127 9813.93194 46504.63513
128 76114.87432 9813.93194
129 -9461.96886 76114.87432
130 44028.30456 -9461.96886
131 18069.94619 44028.30456
132 -21910.06408 18069.94619
133 -84678.29933 -21910.06408
134 74769.34700 -84678.29933
135 -18358.60217 74769.34700
136 53221.84025 -18358.60217
137 -17263.26914 53221.84025
138 19864.04314 -17263.26914
139 -5296.89235 19864.04314
140 4084.69626 -5296.89235
141 77852.89074 4084.69626
142 -24060.25778 77852.89074
143 45184.17555 -24060.25778
144 4112.84198 45184.17555
145 -140942.56072 4112.84198
146 -8201.88223 -140942.56072
147 -43130.13321 -8201.88223
148 -2816.98585 -43130.13321
149 30784.69957 -2816.98585
150 32116.33323 30784.69957
151 -8299.92624 32116.33323
152 8033.78636 -8299.92624
153 6777.32192 8033.78636
154 -11290.90673 6777.32192
155 27366.05699 -11290.90673
156 9257.04231 27366.05699
157 15465.12192 9257.04231
158 -21185.85863 15465.12192
159 -17003.40718 -21185.85863
160 -67.44757 -17003.40718
161 57953.02609 -67.44757
162 14628.78481 57953.02609
163 -2769.77288 14628.78481
164 9235.64174 -2769.77288
165 74812.83975 9235.64174
166 -17397.83892 74812.83975
167 5077.38828 -17397.83892
168 -32942.16090 5077.38828
169 -4659.17680 -32942.16090
170 1296.87281 -4659.17680
171 -4620.43671 1296.87281
172 -48583.89365 -4620.43671
173 -8758.10844 -48583.89365
174 -29446.55405 -8758.10844
175 -38260.27712 -29446.55405
176 -18316.87619 -38260.27712
177 -21318.45870 -18316.87619
178 32099.01134 -21318.45870
179 -197.41986 32099.01134
180 -7535.99743 -197.41986
181 31453.83130 -7535.99743
182 -40372.39380 31453.83130
183 -3936.39313 -40372.39380
184 91674.56454 -3936.39313
185 56556.36880 91674.56454
186 13913.78512 56556.36880
187 41263.23651 13913.78512
188 -28888.17358 41263.23651
189 -56463.25937 -28888.17358
190 32741.89978 -56463.25937
191 23596.56892 32741.89978
192 -13683.30971 23596.56892
193 -11844.13686 -13683.30971
194 -6578.13190 -11844.13686
195 2994.31556 -6578.13190
196 -4331.97509 2994.31556
197 -20870.56016 -4331.97509
198 -11678.83263 -20870.56016
199 -30629.77031 -11678.83263
200 -15191.28980 -30629.77031
201 9245.47919 -15191.28980
202 11608.19225 9245.47919
203 -4636.16253 11608.19225
204 5766.64234 -4636.16253
205 -648.12621 5766.64234
206 -14621.73170 -648.12621
207 68980.60731 -14621.73170
208 34768.15792 68980.60731
209 11349.48024 34768.15792
210 17434.07082 11349.48024
211 26645.05345 17434.07082
212 -5531.46348 26645.05345
213 -18745.51815 -5531.46348
214 -7130.07907 -18745.51815
215 -11118.43158 -7130.07907
216 -23431.43325 -11118.43158
217 -13116.29909 -23431.43325
218 2516.99865 -13116.29909
219 24102.94805 2516.99865
220 -13167.41281 24102.94805
221 -18140.11030 -13167.41281
222 -14953.22079 -18140.11030
223 -6781.22634 -14953.22079
224 -66.40701 -6781.22634
225 23742.48012 -66.40701
226 10099.83407 23742.48012
227 -40481.02481 10099.83407
228 -17080.21435 -40481.02481
229 -39116.09077 -17080.21435
230 -4305.32299 -39116.09077
231 -6779.63091 -4305.32299
232 -19218.07931 -6779.63091
233 1423.44661 -19218.07931
234 -19157.17278 1423.44661
235 -36593.62699 -19157.17278
236 73629.93575 -36593.62699
237 13886.18000 73629.93575
238 9303.29753 13886.18000
239 -20347.05591 9303.29753
240 23903.26613 -20347.05591
241 -36753.74286 23903.26613
242 -33176.27828 -36753.74286
243 -20446.08614 -33176.27828
244 -4630.64885 -20446.08614
245 5682.26255 -4630.64885
246 -18105.81032 5682.26255
247 13734.76252 -18105.81032
248 2463.30507 13734.76252
249 -21110.09935 2463.30507
250 29273.58266 -21110.09935
251 -5225.36905 29273.58266
252 -8960.60088 -5225.36905
253 8875.09866 -8960.60088
254 9166.80623 8875.09866
255 4101.44915 9166.80623
256 -23445.87532 4101.44915
257 12375.60503 -23445.87532
258 7102.70755 12375.60503
259 -7862.37908 7102.70755
260 11607.34998 -7862.37908
261 -17675.65689 11607.34998
262 9881.54942 -17675.65689
263 -6659.74271 9881.54942
264 -31730.01955 -6659.74271
265 10749.04020 -31730.01955
266 -27632.85392 10749.04020
267 -17408.91446 -27632.85392
268 36395.43933 -17408.91446
269 -16256.13556 36395.43933
270 20797.10493 -16256.13556
271 -5679.15563 20797.10493
272 15126.60058 -5679.15563
273 -256.45944 15126.60058
274 4052.73283 -256.45944
275 -3364.61545 4052.73283
276 7251.78743 -3364.61545
277 -7029.69052 7251.78743
278 3680.53941 -7029.69052
279 20760.10145 3680.53941
280 2926.04372 20760.10145
281 -2831.39672 2926.04372
282 24339.39886 -2831.39672
283 13937.47214 24339.39886
284 7167.16670 13937.47214
285 1697.29167 7167.16670
286 13871.40964 1697.29167
287 -18905.86587 13871.40964
288 28402.17160 -18905.86587
289 NA 28402.17160
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -44488.12297 20354.31101
[2,] 3719.15459 -44488.12297
[3,] -62335.24750 3719.15459
[4,] -148.97617 -62335.24750
[5,] -25502.93817 -148.97617
[6,] 132531.04483 -25502.93817
[7,] -18085.04372 132531.04483
[8,] 4467.06262 -18085.04372
[9,] 21656.50433 4467.06262
[10,] 24127.59773 21656.50433
[11,] -60107.54490 24127.59773
[12,] -12817.97456 -60107.54490
[13,] 35554.93488 -12817.97456
[14,] 8366.12334 35554.93488
[15,] -35786.18694 8366.12334
[16,] 15251.84694 -35786.18694
[17,] 5619.29785 15251.84694
[18,] -32816.70385 5619.29785
[19,] -35291.70092 -32816.70385
[20,] -2352.50021 -35291.70092
[21,] 145808.63248 -2352.50021
[22,] 23586.00784 145808.63248
[23,] -62011.14785 23586.00784
[24,] -81966.05035 -62011.14785
[25,] -40908.01894 -81966.05035
[26,] -3834.93329 -40908.01894
[27,] -1495.25631 -3834.93329
[28,] -846.09616 -1495.25631
[29,] 18482.41975 -846.09616
[30,] -6024.21642 18482.41975
[31,] 1886.75957 -6024.21642
[32,] 8276.90486 1886.75957
[33,] -39490.89054 8276.90486
[34,] 58895.24659 -39490.89054
[35,] 51149.04463 58895.24659
[36,] 95487.99097 51149.04463
[37,] 5876.54405 95487.99097
[38,] 17958.59703 5876.54405
[39,] -6896.14006 17958.59703
[40,] 55967.59211 -6896.14006
[41,] -12674.27234 55967.59211
[42,] -9840.93440 -12674.27234
[43,] -7150.72298 -9840.93440
[44,] -24829.37116 -7150.72298
[45,] 125535.17057 -24829.37116
[46,] -21392.94355 125535.17057
[47,] -32258.47834 -21392.94355
[48,] 13163.93870 -32258.47834
[49,] -31364.87975 13163.93870
[50,] -15340.22014 -31364.87975
[51,] -17913.01979 -15340.22014
[52,] -27940.91442 -17913.01979
[53,] -8797.95560 -27940.91442
[54,] -10192.66940 -8797.95560
[55,] 52258.63519 -10192.66940
[56,] -1051.48196 52258.63519
[57,] -24725.69809 -1051.48196
[58,] -16252.77860 -24725.69809
[59,] 19653.85262 -16252.77860
[60,] 20572.36971 19653.85262
[61,] -207.88316 20572.36971
[62,] 3398.36601 -207.88316
[63,] 31021.74756 3398.36601
[64,] 47568.85201 31021.74756
[65,] 14684.85135 47568.85201
[66,] -65824.07218 14684.85135
[67,] -46113.23293 -65824.07218
[68,] -30145.75625 -46113.23293
[69,] -85338.48905 -30145.75625
[70,] -6747.03318 -85338.48905
[71,] -14982.92296 -6747.03318
[72,] 6134.06359 -14982.92296
[73,] 9118.57421 6134.06359
[74,] -58287.01294 9118.57421
[75,] 47578.38570 -58287.01294
[76,] 37564.18407 47578.38570
[77,] -47789.23968 37564.18407
[78,] -54034.88373 -47789.23968
[79,] -9360.04375 -54034.88373
[80,] -3704.90591 -9360.04375
[81,] 90255.35014 -3704.90591
[82,] 16607.14188 90255.35014
[83,] -24506.70424 16607.14188
[84,] -13818.29789 -24506.70424
[85,] 23355.79571 -13818.29789
[86,] -34048.52078 23355.79571
[87,] 57660.08995 -34048.52078
[88,] 34877.82348 57660.08995
[89,] -129421.79281 34877.82348
[90,] 32397.98203 -129421.79281
[91,] -54601.76027 32397.98203
[92,] 18830.55055 -54601.76027
[93,] 18277.34064 18830.55055
[94,] 71710.70698 18277.34064
[95,] 4656.51087 71710.70698
[96,] 4953.10149 4656.51087
[97,] -14956.90403 4953.10149
[98,] -29688.71412 -14956.90403
[99,] 48624.57912 -29688.71412
[100,] -16536.24252 48624.57912
[101,] 5399.17628 -16536.24252
[102,] -50954.74810 5399.17628
[103,] -21280.23837 -50954.74810
[104,] 3370.85240 -21280.23837
[105,] -53686.39445 3370.85240
[106,] 7768.57031 -53686.39445
[107,] -27812.67002 7768.57031
[108,] -37879.09924 -27812.67002
[109,] -104416.40689 -37879.09924
[110,] 62891.25590 -104416.40689
[111,] -12912.29012 62891.25590
[112,] -4091.45542 -12912.29012
[113,] -54861.35779 -4091.45542
[114,] -4283.58241 -54861.35779
[115,] -25104.17968 -4283.58241
[116,] 81225.13093 -25104.17968
[117,] -1883.71483 81225.13093
[118,] 65501.09984 -1883.71483
[119,] -17487.21729 65501.09984
[120,] 14839.01738 -17487.21729
[121,] 5115.50768 14839.01738
[122,] -24631.40670 5115.50768
[123,] -9077.39332 -24631.40670
[124,] -20708.39322 -9077.39332
[125,] 11534.82127 -20708.39322
[126,] 46504.63513 11534.82127
[127,] 9813.93194 46504.63513
[128,] 76114.87432 9813.93194
[129,] -9461.96886 76114.87432
[130,] 44028.30456 -9461.96886
[131,] 18069.94619 44028.30456
[132,] -21910.06408 18069.94619
[133,] -84678.29933 -21910.06408
[134,] 74769.34700 -84678.29933
[135,] -18358.60217 74769.34700
[136,] 53221.84025 -18358.60217
[137,] -17263.26914 53221.84025
[138,] 19864.04314 -17263.26914
[139,] -5296.89235 19864.04314
[140,] 4084.69626 -5296.89235
[141,] 77852.89074 4084.69626
[142,] -24060.25778 77852.89074
[143,] 45184.17555 -24060.25778
[144,] 4112.84198 45184.17555
[145,] -140942.56072 4112.84198
[146,] -8201.88223 -140942.56072
[147,] -43130.13321 -8201.88223
[148,] -2816.98585 -43130.13321
[149,] 30784.69957 -2816.98585
[150,] 32116.33323 30784.69957
[151,] -8299.92624 32116.33323
[152,] 8033.78636 -8299.92624
[153,] 6777.32192 8033.78636
[154,] -11290.90673 6777.32192
[155,] 27366.05699 -11290.90673
[156,] 9257.04231 27366.05699
[157,] 15465.12192 9257.04231
[158,] -21185.85863 15465.12192
[159,] -17003.40718 -21185.85863
[160,] -67.44757 -17003.40718
[161,] 57953.02609 -67.44757
[162,] 14628.78481 57953.02609
[163,] -2769.77288 14628.78481
[164,] 9235.64174 -2769.77288
[165,] 74812.83975 9235.64174
[166,] -17397.83892 74812.83975
[167,] 5077.38828 -17397.83892
[168,] -32942.16090 5077.38828
[169,] -4659.17680 -32942.16090
[170,] 1296.87281 -4659.17680
[171,] -4620.43671 1296.87281
[172,] -48583.89365 -4620.43671
[173,] -8758.10844 -48583.89365
[174,] -29446.55405 -8758.10844
[175,] -38260.27712 -29446.55405
[176,] -18316.87619 -38260.27712
[177,] -21318.45870 -18316.87619
[178,] 32099.01134 -21318.45870
[179,] -197.41986 32099.01134
[180,] -7535.99743 -197.41986
[181,] 31453.83130 -7535.99743
[182,] -40372.39380 31453.83130
[183,] -3936.39313 -40372.39380
[184,] 91674.56454 -3936.39313
[185,] 56556.36880 91674.56454
[186,] 13913.78512 56556.36880
[187,] 41263.23651 13913.78512
[188,] -28888.17358 41263.23651
[189,] -56463.25937 -28888.17358
[190,] 32741.89978 -56463.25937
[191,] 23596.56892 32741.89978
[192,] -13683.30971 23596.56892
[193,] -11844.13686 -13683.30971
[194,] -6578.13190 -11844.13686
[195,] 2994.31556 -6578.13190
[196,] -4331.97509 2994.31556
[197,] -20870.56016 -4331.97509
[198,] -11678.83263 -20870.56016
[199,] -30629.77031 -11678.83263
[200,] -15191.28980 -30629.77031
[201,] 9245.47919 -15191.28980
[202,] 11608.19225 9245.47919
[203,] -4636.16253 11608.19225
[204,] 5766.64234 -4636.16253
[205,] -648.12621 5766.64234
[206,] -14621.73170 -648.12621
[207,] 68980.60731 -14621.73170
[208,] 34768.15792 68980.60731
[209,] 11349.48024 34768.15792
[210,] 17434.07082 11349.48024
[211,] 26645.05345 17434.07082
[212,] -5531.46348 26645.05345
[213,] -18745.51815 -5531.46348
[214,] -7130.07907 -18745.51815
[215,] -11118.43158 -7130.07907
[216,] -23431.43325 -11118.43158
[217,] -13116.29909 -23431.43325
[218,] 2516.99865 -13116.29909
[219,] 24102.94805 2516.99865
[220,] -13167.41281 24102.94805
[221,] -18140.11030 -13167.41281
[222,] -14953.22079 -18140.11030
[223,] -6781.22634 -14953.22079
[224,] -66.40701 -6781.22634
[225,] 23742.48012 -66.40701
[226,] 10099.83407 23742.48012
[227,] -40481.02481 10099.83407
[228,] -17080.21435 -40481.02481
[229,] -39116.09077 -17080.21435
[230,] -4305.32299 -39116.09077
[231,] -6779.63091 -4305.32299
[232,] -19218.07931 -6779.63091
[233,] 1423.44661 -19218.07931
[234,] -19157.17278 1423.44661
[235,] -36593.62699 -19157.17278
[236,] 73629.93575 -36593.62699
[237,] 13886.18000 73629.93575
[238,] 9303.29753 13886.18000
[239,] -20347.05591 9303.29753
[240,] 23903.26613 -20347.05591
[241,] -36753.74286 23903.26613
[242,] -33176.27828 -36753.74286
[243,] -20446.08614 -33176.27828
[244,] -4630.64885 -20446.08614
[245,] 5682.26255 -4630.64885
[246,] -18105.81032 5682.26255
[247,] 13734.76252 -18105.81032
[248,] 2463.30507 13734.76252
[249,] -21110.09935 2463.30507
[250,] 29273.58266 -21110.09935
[251,] -5225.36905 29273.58266
[252,] -8960.60088 -5225.36905
[253,] 8875.09866 -8960.60088
[254,] 9166.80623 8875.09866
[255,] 4101.44915 9166.80623
[256,] -23445.87532 4101.44915
[257,] 12375.60503 -23445.87532
[258,] 7102.70755 12375.60503
[259,] -7862.37908 7102.70755
[260,] 11607.34998 -7862.37908
[261,] -17675.65689 11607.34998
[262,] 9881.54942 -17675.65689
[263,] -6659.74271 9881.54942
[264,] -31730.01955 -6659.74271
[265,] 10749.04020 -31730.01955
[266,] -27632.85392 10749.04020
[267,] -17408.91446 -27632.85392
[268,] 36395.43933 -17408.91446
[269,] -16256.13556 36395.43933
[270,] 20797.10493 -16256.13556
[271,] -5679.15563 20797.10493
[272,] 15126.60058 -5679.15563
[273,] -256.45944 15126.60058
[274,] 4052.73283 -256.45944
[275,] -3364.61545 4052.73283
[276,] 7251.78743 -3364.61545
[277,] -7029.69052 7251.78743
[278,] 3680.53941 -7029.69052
[279,] 20760.10145 3680.53941
[280,] 2926.04372 20760.10145
[281,] -2831.39672 2926.04372
[282,] 24339.39886 -2831.39672
[283,] 13937.47214 24339.39886
[284,] 7167.16670 13937.47214
[285,] 1697.29167 7167.16670
[286,] 13871.40964 1697.29167
[287,] -18905.86587 13871.40964
[288,] 28402.17160 -18905.86587
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -44488.12297 20354.31101
2 3719.15459 -44488.12297
3 -62335.24750 3719.15459
4 -148.97617 -62335.24750
5 -25502.93817 -148.97617
6 132531.04483 -25502.93817
7 -18085.04372 132531.04483
8 4467.06262 -18085.04372
9 21656.50433 4467.06262
10 24127.59773 21656.50433
11 -60107.54490 24127.59773
12 -12817.97456 -60107.54490
13 35554.93488 -12817.97456
14 8366.12334 35554.93488
15 -35786.18694 8366.12334
16 15251.84694 -35786.18694
17 5619.29785 15251.84694
18 -32816.70385 5619.29785
19 -35291.70092 -32816.70385
20 -2352.50021 -35291.70092
21 145808.63248 -2352.50021
22 23586.00784 145808.63248
23 -62011.14785 23586.00784
24 -81966.05035 -62011.14785
25 -40908.01894 -81966.05035
26 -3834.93329 -40908.01894
27 -1495.25631 -3834.93329
28 -846.09616 -1495.25631
29 18482.41975 -846.09616
30 -6024.21642 18482.41975
31 1886.75957 -6024.21642
32 8276.90486 1886.75957
33 -39490.89054 8276.90486
34 58895.24659 -39490.89054
35 51149.04463 58895.24659
36 95487.99097 51149.04463
37 5876.54405 95487.99097
38 17958.59703 5876.54405
39 -6896.14006 17958.59703
40 55967.59211 -6896.14006
41 -12674.27234 55967.59211
42 -9840.93440 -12674.27234
43 -7150.72298 -9840.93440
44 -24829.37116 -7150.72298
45 125535.17057 -24829.37116
46 -21392.94355 125535.17057
47 -32258.47834 -21392.94355
48 13163.93870 -32258.47834
49 -31364.87975 13163.93870
50 -15340.22014 -31364.87975
51 -17913.01979 -15340.22014
52 -27940.91442 -17913.01979
53 -8797.95560 -27940.91442
54 -10192.66940 -8797.95560
55 52258.63519 -10192.66940
56 -1051.48196 52258.63519
57 -24725.69809 -1051.48196
58 -16252.77860 -24725.69809
59 19653.85262 -16252.77860
60 20572.36971 19653.85262
61 -207.88316 20572.36971
62 3398.36601 -207.88316
63 31021.74756 3398.36601
64 47568.85201 31021.74756
65 14684.85135 47568.85201
66 -65824.07218 14684.85135
67 -46113.23293 -65824.07218
68 -30145.75625 -46113.23293
69 -85338.48905 -30145.75625
70 -6747.03318 -85338.48905
71 -14982.92296 -6747.03318
72 6134.06359 -14982.92296
73 9118.57421 6134.06359
74 -58287.01294 9118.57421
75 47578.38570 -58287.01294
76 37564.18407 47578.38570
77 -47789.23968 37564.18407
78 -54034.88373 -47789.23968
79 -9360.04375 -54034.88373
80 -3704.90591 -9360.04375
81 90255.35014 -3704.90591
82 16607.14188 90255.35014
83 -24506.70424 16607.14188
84 -13818.29789 -24506.70424
85 23355.79571 -13818.29789
86 -34048.52078 23355.79571
87 57660.08995 -34048.52078
88 34877.82348 57660.08995
89 -129421.79281 34877.82348
90 32397.98203 -129421.79281
91 -54601.76027 32397.98203
92 18830.55055 -54601.76027
93 18277.34064 18830.55055
94 71710.70698 18277.34064
95 4656.51087 71710.70698
96 4953.10149 4656.51087
97 -14956.90403 4953.10149
98 -29688.71412 -14956.90403
99 48624.57912 -29688.71412
100 -16536.24252 48624.57912
101 5399.17628 -16536.24252
102 -50954.74810 5399.17628
103 -21280.23837 -50954.74810
104 3370.85240 -21280.23837
105 -53686.39445 3370.85240
106 7768.57031 -53686.39445
107 -27812.67002 7768.57031
108 -37879.09924 -27812.67002
109 -104416.40689 -37879.09924
110 62891.25590 -104416.40689
111 -12912.29012 62891.25590
112 -4091.45542 -12912.29012
113 -54861.35779 -4091.45542
114 -4283.58241 -54861.35779
115 -25104.17968 -4283.58241
116 81225.13093 -25104.17968
117 -1883.71483 81225.13093
118 65501.09984 -1883.71483
119 -17487.21729 65501.09984
120 14839.01738 -17487.21729
121 5115.50768 14839.01738
122 -24631.40670 5115.50768
123 -9077.39332 -24631.40670
124 -20708.39322 -9077.39332
125 11534.82127 -20708.39322
126 46504.63513 11534.82127
127 9813.93194 46504.63513
128 76114.87432 9813.93194
129 -9461.96886 76114.87432
130 44028.30456 -9461.96886
131 18069.94619 44028.30456
132 -21910.06408 18069.94619
133 -84678.29933 -21910.06408
134 74769.34700 -84678.29933
135 -18358.60217 74769.34700
136 53221.84025 -18358.60217
137 -17263.26914 53221.84025
138 19864.04314 -17263.26914
139 -5296.89235 19864.04314
140 4084.69626 -5296.89235
141 77852.89074 4084.69626
142 -24060.25778 77852.89074
143 45184.17555 -24060.25778
144 4112.84198 45184.17555
145 -140942.56072 4112.84198
146 -8201.88223 -140942.56072
147 -43130.13321 -8201.88223
148 -2816.98585 -43130.13321
149 30784.69957 -2816.98585
150 32116.33323 30784.69957
151 -8299.92624 32116.33323
152 8033.78636 -8299.92624
153 6777.32192 8033.78636
154 -11290.90673 6777.32192
155 27366.05699 -11290.90673
156 9257.04231 27366.05699
157 15465.12192 9257.04231
158 -21185.85863 15465.12192
159 -17003.40718 -21185.85863
160 -67.44757 -17003.40718
161 57953.02609 -67.44757
162 14628.78481 57953.02609
163 -2769.77288 14628.78481
164 9235.64174 -2769.77288
165 74812.83975 9235.64174
166 -17397.83892 74812.83975
167 5077.38828 -17397.83892
168 -32942.16090 5077.38828
169 -4659.17680 -32942.16090
170 1296.87281 -4659.17680
171 -4620.43671 1296.87281
172 -48583.89365 -4620.43671
173 -8758.10844 -48583.89365
174 -29446.55405 -8758.10844
175 -38260.27712 -29446.55405
176 -18316.87619 -38260.27712
177 -21318.45870 -18316.87619
178 32099.01134 -21318.45870
179 -197.41986 32099.01134
180 -7535.99743 -197.41986
181 31453.83130 -7535.99743
182 -40372.39380 31453.83130
183 -3936.39313 -40372.39380
184 91674.56454 -3936.39313
185 56556.36880 91674.56454
186 13913.78512 56556.36880
187 41263.23651 13913.78512
188 -28888.17358 41263.23651
189 -56463.25937 -28888.17358
190 32741.89978 -56463.25937
191 23596.56892 32741.89978
192 -13683.30971 23596.56892
193 -11844.13686 -13683.30971
194 -6578.13190 -11844.13686
195 2994.31556 -6578.13190
196 -4331.97509 2994.31556
197 -20870.56016 -4331.97509
198 -11678.83263 -20870.56016
199 -30629.77031 -11678.83263
200 -15191.28980 -30629.77031
201 9245.47919 -15191.28980
202 11608.19225 9245.47919
203 -4636.16253 11608.19225
204 5766.64234 -4636.16253
205 -648.12621 5766.64234
206 -14621.73170 -648.12621
207 68980.60731 -14621.73170
208 34768.15792 68980.60731
209 11349.48024 34768.15792
210 17434.07082 11349.48024
211 26645.05345 17434.07082
212 -5531.46348 26645.05345
213 -18745.51815 -5531.46348
214 -7130.07907 -18745.51815
215 -11118.43158 -7130.07907
216 -23431.43325 -11118.43158
217 -13116.29909 -23431.43325
218 2516.99865 -13116.29909
219 24102.94805 2516.99865
220 -13167.41281 24102.94805
221 -18140.11030 -13167.41281
222 -14953.22079 -18140.11030
223 -6781.22634 -14953.22079
224 -66.40701 -6781.22634
225 23742.48012 -66.40701
226 10099.83407 23742.48012
227 -40481.02481 10099.83407
228 -17080.21435 -40481.02481
229 -39116.09077 -17080.21435
230 -4305.32299 -39116.09077
231 -6779.63091 -4305.32299
232 -19218.07931 -6779.63091
233 1423.44661 -19218.07931
234 -19157.17278 1423.44661
235 -36593.62699 -19157.17278
236 73629.93575 -36593.62699
237 13886.18000 73629.93575
238 9303.29753 13886.18000
239 -20347.05591 9303.29753
240 23903.26613 -20347.05591
241 -36753.74286 23903.26613
242 -33176.27828 -36753.74286
243 -20446.08614 -33176.27828
244 -4630.64885 -20446.08614
245 5682.26255 -4630.64885
246 -18105.81032 5682.26255
247 13734.76252 -18105.81032
248 2463.30507 13734.76252
249 -21110.09935 2463.30507
250 29273.58266 -21110.09935
251 -5225.36905 29273.58266
252 -8960.60088 -5225.36905
253 8875.09866 -8960.60088
254 9166.80623 8875.09866
255 4101.44915 9166.80623
256 -23445.87532 4101.44915
257 12375.60503 -23445.87532
258 7102.70755 12375.60503
259 -7862.37908 7102.70755
260 11607.34998 -7862.37908
261 -17675.65689 11607.34998
262 9881.54942 -17675.65689
263 -6659.74271 9881.54942
264 -31730.01955 -6659.74271
265 10749.04020 -31730.01955
266 -27632.85392 10749.04020
267 -17408.91446 -27632.85392
268 36395.43933 -17408.91446
269 -16256.13556 36395.43933
270 20797.10493 -16256.13556
271 -5679.15563 20797.10493
272 15126.60058 -5679.15563
273 -256.45944 15126.60058
274 4052.73283 -256.45944
275 -3364.61545 4052.73283
276 7251.78743 -3364.61545
277 -7029.69052 7251.78743
278 3680.53941 -7029.69052
279 20760.10145 3680.53941
280 2926.04372 20760.10145
281 -2831.39672 2926.04372
282 24339.39886 -2831.39672
283 13937.47214 24339.39886
284 7167.16670 13937.47214
285 1697.29167 7167.16670
286 13871.40964 1697.29167
287 -18905.86587 13871.40964
288 28402.17160 -18905.86587
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7ejwb1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8iypw1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9wmyq1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10rivq1323955355.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11ygvv1323955355.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/121v231323955355.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1329hm1323955355.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14ztae1323955355.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15c7qv1323955355.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/165gs21323955355.tab")
+ }
>
> try(system("convert tmp/1exw11323955355.ps tmp/1exw11323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u5k41323955355.ps tmp/2u5k41323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/3yfl41323955355.ps tmp/3yfl41323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xk071323955355.ps tmp/4xk071323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/5166e1323955355.ps tmp/5166e1323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/6kqbn1323955355.ps tmp/6kqbn1323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ejwb1323955355.ps tmp/7ejwb1323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/8iypw1323955355.ps tmp/8iypw1323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wmyq1323955355.ps tmp/9wmyq1323955355.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rivq1323955355.ps tmp/10rivq1323955355.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
11.876 0.722 12.622